boot_model: Bootstrap optimism correction for models

In David-Hervas/repmod: Create Report Table from Different Objects

Bootstrap optimism correction for models

Description

Returns optimism correction for absolute fit values

Usage

boot_model(
  formula,
  data,
  B = 200,
  fit_function = "lm",
  metric = if (length(unique(data[, as.character(formula)[2]])) == 2) "AUC" else "RMSE",
  predict.control = list(NULL),
  ...
)

Arguments

formula	An object of class "formula" describing the model to be validated
data	A data frame containing the variables specified in formula argument
B	Number of bootstrap samples
fit_function	Name of the model fitting function
metric	Performance metric to estimate: RMSE, MSE, MAE or AUC
predict.control	Named list of arguments to pass to the predict function of the model
...	Further arguments passed to the model fitting function

Value

Optimism correction values for the selected performance metric

Examples

boot_model(Petal.Length ~ Sepal.Width + Species, data=iris)

David-Hervas/repmod documentation built on Feb. 3, 2025, 11:38 a.m.